Document Extension in Dictation-Based Document Generation Workflow

ABSTRACT

An automatic speech recognizer is used to produce a structured document representing the contents of human speech. A best practice is applied to the structured document to produce a conclusion, such as a conclusion that required information is missing from the structured document. Content is inserted into the structured document based on the conclusion, thereby producing a modified document. The inserted content may be obtained by prompting a human user for the content and receiving input representing the content from the human user.

BACKGROUND

A variety of automatic speech recognition (ASR) systems exist forrecognizing speech and for generating text and/or commands based on suchspeech. ASR systems that generate text based on speech are typicallyreferred to as “dictation” or “transcription” systems.

Some dictation systems allow users to dictate freeform text that isentered directly into documents exactly as spoken, except possibly withspelling corrections or other minor corrections applied. A commonexample of such systems is the dictation systems commonly used inconjunction with word processors to dictate memos, articles, and otherprose documents. In contrast, some dictation systems are designed togenerate and input data in a structured format based on the user'sspeech. For example, such an ASR system may be used to enter data into adatabase form, in which data in each field is constrained to have onlycertain values and to be represented in certain formats. For example, a“Priority” field in such a form may be associated with a dropdown listhaving only three values, such as “High,” “Medium,” and “Low,” in whichcase the speech of a user dictating into such a field may be constrainedto produce only one of these three possibilities as speech recognitionresults.

Whether the user provides input using speech input or other kinds ofinput (such as mouse or keyboard input), both freeform and structuredinput modalities have a variety of advantages and disadvantages. Forexample, one advantage of freeform input modalities is that they allowthe user to provide a wide range of input and therefore to capturesubtleties in the information provided. A corresponding disadvantage ofstructured input modalities is that by constraining the input optionsavailable to the user, they may fail to capture information that cannotaccurately be represented using the available options.

One advantage of structured input modalities is that they require datato be stored in the form of discrete data elements that computers canact on easily and automatically. For example, if a patient has anallergy to allergen X and currently takes medication Y, if these twofacts are input using structured input modalities (such as by usingdropdown lists for selecting allergens and medications, respectively),then the resulting data can be encoded in discrete data elementsrepresenting allergen X and medication Y, respectively, and a computercan performing processing on such information easily and automatically,such as by comparing the data to contraindications on a predeterminedlist to determine whether allergen X is contraindicated with medicationY. Structured input modalities, in other words, enable data to be inputin a form such that the meaning of the data is available to andunambiguously processable by a computer without the need for furtherinterpretation. In contrast, data input using freeform input modalities(such as the text “the patient is allergic to X and is taking medicationY”) must be parsed and interpreted in an attempt to discern the meaningof the text before a computer can attempt to parse the informationrepresented by the text. Such parsing and interpretation are subject toerrors which can impede the ability to perform the kind of processingthat can be performed easily and automatically using data obtained usingstructured input modalities.

Another advantage of structured input modalities is that they can enabledata to be input with fewer errors because the user is prevented, forexample, from providing the wrong type of information (such as byinputting a name into a date field) or from providing information thatis outside a permissible range of values (such as by entering −10 into afield representing the body temperature of a patient). A correspondingdisadvantage of freeform input modalities is that they can allow inputto contain a wide variety of errors because the user's input is notconstrained.

Yet another advantage of freeform input modalities is that they do notpredispose the user toward providing any one particular input overanother. In contrast, structured input modalities can bias the inputprovided by the user towards the set or range of permitted inputs. Thisbias can be undesirable when the goal of the system is to faithfullycapture and represent information. For example, a documentation systemthat only offers a checkbox as a means for inputting information aboutthe presence or absence of a particular fact—such as whether a patienthas hypertension—forces the user to pigeonhole the user's knowledgeabout the patient's condition into a binary value of “yes” or “no.” Ifthe user's knowledge of the patient indicates, for example, that thepatient currently has mild hypertension, that the patient may possiblyhave hypertension, or that the patient is in the process of developinghypertension, then requiring the user to provide an answer of “yes” or“no” to the question, “Does the patient have hypertension?,” will resultin a misrepresentation of the true state of the patient in relation tohypertension.

Some input systems (such as EMR systems) attempt to address this problemby adding additional input choices, such as by enabling the user toprovide not only binary answers to questions about facts, but also toprovide information about additional qualities related to those facts,such as degree, likelihood, conditionality, and interdependency of suchfacts. For example, such a system might require the user to provide a“yes” or “no” answer to the question, “Does the patient havehypertension?,” but also ask the user, in connection with that question,to provide a degree to which the user's “yes” or “no” answer is correct,a likelihood that the user's “yes” or “no” answer is correct, and so on.

Although this kind of solution can address some of the problems withstructured input modalities, adding such additional input choices canquickly make using the system unwieldy due to the large amount andvariety of inputs that the user must provide. Furthermore, the meaningsof the additional input choices may not be clear to the usersresponsible for selecting such choices. For example, if the user isprovided with choices of “Low,” “Medium,” and “High” for rating thelikelihood that the patient has hypertension, it is not clear whetherthese choices represent equally-distributed probabilities such as0-33.3%, 33.3-66.7%, and 66.7-100%, or some other ranges, such as 0-10%,10-90%, and 90-100%. As a result, the user must make some decision abouthow to interpret the available input choices, and the result of thatdecision may differ both from that intended by the designer of thesystem and from the decisions made by other users when faced with thesame set of input choices. As a result, the inputs provided by users mayresult in inaccurate information being entered into the system.

In light of these various advantages and disadvantages of freeform andstructured input modalities, what is needed are improved techniques forcapturing data to maximize accuracy and minimize errors.

SUMMARY

In one aspect, a method includes applying automatic speech recognitionto an audio signal to produce a structured document representingcontents of the audio signal. The method includes determining whetherthe structured document includes an indication of compliance with a bestpractice to produce a conclusion. The method includes inserting contentinto the structured document, based on the conclusion, to produce amodified structured document.

In another aspect, a system includes an automatic speech recognitionsystem and a structured document analyzer. The automatic speechrecognition system applies automatic speech recognition to an audiosignal to produce a structured document representing contents of theaudio signal. The automatic speech recognition system may include astructured document generator producing the structured document. Thestructured document analyzer determines whether the structured documentincludes an indication of compliance with a best practice to produce aconclusion and inserting content into the structured document, based onthe conclusion, to produce a modified structured document.

Other features and advantages of various aspects and embodiments of thepresent invention will become apparent from the following descriptionand from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, aspects, features, and advantages ofthe disclosure will become more apparent and better understood byreferring to the following description taken in conjunction with theaccompanying drawings, in which:

FIG. 1A is a block diagram depicting one embodiment of a system fordocument extension in dictation-based document generation workflow;

FIG. 1B is a block diagram depicting one embodiment of a structureddocument representing contents of an audio signal;

FIG. 1C is a block diagram depicting one embodiment of a system fordocument extension in dictation-based document generation workflow;

FIG. 1D is a block diagram depicting one embodiment of a structureddocument modified to request additional content; and

FIG. 2 is a flow diagram depicting one embodiment of a method fordocument extension in dictation-based document generation workflow.

DETAILED DESCRIPTION

As described above, freeform and structured input modalities have avariety of advantages and disadvantages. In particular, it was mentionedthat a structured input modality can bias the user toward providing theparticular inputs that the structured input modality permits, therebypotentially causing inaccurate data to be generated. The bias imposed bystructured input modalities, however, is not always harmful. In somecircumstances it can have beneficial effects. For example, by forcingusers to commit to certain discrete input choices, such as a particulardiagnosis in the case of an electronic medical record, the resultingdata may be less accurate but more unambiguous than it would have beenif a freeform input modality had been used. Despite the potentialdecrease in accuracy that results from requiring input to be selectedfrom among a discrete set of permissible inputs, forcing the user tomake such a selection may cause the physician or other user to make thecrucial decision about which discrete input to select early in theprocess (namely, at the time of providing the input), rather thanleaving such a certain to the same user, or to a different and lessqualified user, at a later date. As a result, the resulting data may bemore likely to be useful for making accurate decisions without the needfor further review or revision in certain circumstances, such as whenthe input data is to be used to submit a medical report to a payer for atreatment plan, if such payer requires specific diagnoses to be providedbefore payment can be made.

As another example, structured input forms can be useful for providingguidance to the user about the set of information that must be providedand about the possible contents of such information. For example, thepresence of a form field containing the question, “Does the patient havehypertension?,” can serve as a reminder to the user that the answer tosuch a question, and possibly other information related to the patientin connection with hypertension, is required. As a result, using formsto create documentation can result in fewer omissions of required ordesirable information than using freeform text input. Because differentforms can be used in different contexts and to create different kinds ofdocumentation, forms can be tailored to prompt the user for theinformation that is relevant and/or required in each context. Therefore,one significant benefit of structured input modalities is that they canreduce the frequency of errors in the form of omissions of relevantand/or required data.

Embodiments of the present invention may be used to obtain the benefitof the advantages of both freeform and structured input modalities,while reducing or eliminating the disadvantages of both such inputmodalities.

Referring now to FIGS. 1A and 1B, in conjunction with FIG. 2, a method200 includes applying automatic speech recognition to an audio signal toproduce a structured document representing contents of the audio signal(210). In particular, embodiments of the present invention may enableusers to dictate information in freeform, as if they were dictating adocument to be transcribed into a freeform transcript. An automaticspeech recognition system 102 may then be used to generate a structureddocument 120 based on the user's speech, where the structured document120 encodes concepts from the user's speech into discrete data elements.For example, the automatic speech recognition system 102 may include astructured document generator 104 receiving an audio signal via an I/Odevice 103 (such as, for example, a microphone) and generating thestructured document 120. As another example, the automatic speechrecognition system 102 may generate a transcription 108 of the audiosignal and provide the transcription 108 to the structured documentgenerator 104 for generation of the structured document 120. As shown inFIG. 1B, the structured document 120 may include a plurality of portions(which may also be referred to as sub-templates, sub-portions ordocument components). A portion in the plurality of portions may or maynot contain information—as shown in FIG. 1B, a first portion 122contains information 124 (e.g., “The doctor ordered blood work fordiabetic Patient Smith”) but the second portion 126 does not contain anyinformation. Examples of techniques that may be used to create suchstructured documents may be found, for example, in commonly-owned U.S.Pat. No. 7,584,103, entitled, “Automated Extraction of Semantic Contentand Generation of a Structured Document from Speech”; commonly-ownedU.S. Pat. No. 7,716,040, entitled, “Verification of Extracted Data”; andthe patents, patent applications, and other documents cited therein.These techniques, however, are merely examples of techniques that may beused to generate a structured document 120 based on speech, and do notconstitute limitations of the present invention.

The method 200 includes determining whether the structured documentincludes an indication of compliance with a best practice to produce aconclusion (220). For example, the automatic speech recognition system102 may include, or be in communication with, a structured documentanalyzer 106 that analyzes the structured document 120 to determinewhether the structured document 120 includes an indication of compliancewith a best practice and produces a conclusion that represents theoutcome of the determination. The structured document analyzer 106 maydetermine that the structured document 120 includes an indication ofcompliancy due to the presence of information within the structureddocument. Alternatively, for example, the structured document analyzer106 may determine that the structured document 120 includes anindication of compliancy due to the absence of information within thestructured document.

The structured document analyzer 106 may determine whether the formand/or content of the structured document 120 include the indication ofcompliance with the best practice (e.g., by determining whether thestructured document 120 contains a particular section or piece ofinformation); in such an embodiment, the structured document analyzer106 may determine whether the contents of the structured document 120comply with the best practice.

Additionally or alternatively, the structured document analyzer 106 maydetermine whether an action or other fact described by the structureddocument 120 complies with the best practice; in such an embodiment, thestructured document analyzer 106 may determine whether a factrepresented by the contents of the structured document 120 complies withthe best practice. As an example, the structured document analyzer 106may determine that to comply with a best practice, a particularstructured document 120 should include an indication as to whether afoot examination was performed during a patient-physician encounter(e.g., the structured document 120 should include a statement such as“During the visit, Dr. Jones performed a foot examination for PatientSmith”); in determining that the structured document 120 includes nosuch indication, or that the structured document 120 includes anindication that no such examination occurred, the structured documentanalyzer 106 may produce a conclusion that the patient-physicianencounter itself did not comply with the best practice since no footexamination was performed.

Once such a structured document 120 has been created, embodiments of thepresent invention may be used to automatically provide context-dependentguidance to encourage the use of best documentation practices by usersof the system, such as the speaker whose speech was recognized to createthe structured document 120 and/or other users who are responsible forediting, reformatting, and proofreading the document. For example,consider a case in which a user speaks into an audio capture device(such as a microphone connected to a desktop computer, or a handheldaudio device containing an embedded microphone, or other input/outputdevice 103) and in which the user has access to a computer monitor (orother display device 105) for reviewing and signing off on the resultingtranscript. While (or after) the user dictates a freeform report intothe audio capture device, any of the techniques referenced above may beused to generate a structured document 120 based on the user's speech.As another example, a user of a computing device 101 b (not shown) mayuse an input/output device 103 to provide audio signals to the computingdevice 101 b; the computing device 101 b may transmit the audio signalsto the computing device 101 shown in FIG. 1A.

An embodiment of the present invention may include or have access toinformation about best practices for use in connection with the reportdictated by the user. Such best practices may, for example, includerules, guidelines, or preferences related to any one or more of thefollowing:

-   -   information that must be included in the report (such as the        patient's name and date of the patient's visit); and    -   actions that are required to be taken before the report can be        completed (such as performing a particular procedure, such as a        foot exam, on the patient during the visit described in the        report).

Embodiments of the present invention may use a single set of bestpractices for all reports, or may use different sets of best practicesto different reports. For example, a distinct set of best practices mayapply to each of a plurality of report types and/or content. For anyparticular report, the set of best practices corresponding to thereport's type (or corresponding to content in the report) may be appliedto the report. As another example, a generic (e.g., universal) set ofbest practices may be applied to all reports in addition to specificsets of best practices based on report types and/or content. These andother examples may be combined with each other in any of a variety ofways.

The best practices may be represented and stored in any of a variety ofways, as will be understood by those having ordinary skill in the art.For example, best practices may take the form of rules that operate ondiscrete data elements in structured reports 120. For example, a bestpractice rule may dictate that if the discrete data elements in astructured report 120 indicate that the patient described by the reporthas diabetes, then the structured report 120 must indicate whether afoot exam was performed on the patient because it is a best practice toperform regular foot exams on diabetic patients. Such rules may operateon freeform text in addition to or instead of discrete data elements.

Best practices need not take the form of rules. Alternatively oradditional for example, they may take the form of heuristics orprocedures for drawing conclusions about whether a particular report ismissing required (or recommended) data, includes data that it isprohibited from including (or that is advisable not to include), orotherwise fails to comply with or falls short of any required or desiredstandard applicable to the report.

The structured document analyzer 106 may identify a best practice basedon data from a variety of sources, such as any one or more of the reportitself, other reports (such as other reports related to the same patientor subject), database records (such as electronic medical records(EMRs)), or any other source of data. For example, the structureddocument analyzer 106 may analyze a data source relating to an event towhich the structured document 120 relates to identify the best practice.

A structured report 120, once created, may be displayed to the user whodictated the report and/or to other users in any of a variety of ways.For example, the structured report 120 may be displayed as a documentcontaining the text of the report, visually structured into sections(such as by adding section headings before each section or byemphasizing dictated section headings), and with discrete data elements(such as dates, medications, allergies, and diagnoses) emphasized orotherwise formatted to indicate that they are discrete data elementsand/or to indicate the types of such discrete data elements. Thestructured report 120, in other words, may be rendered in a format thatgenerally resembles that of a plain text document rendered by aconventional word processor, but with the structured elements of thedocument (e.g., sections and lower-level concepts) visually emphasizedor otherwise indicated.

As mentioned above, the structured document analyzer 106 may produce aconclusion 114, such as a conclusion 114 that certain requiredinformation is missing from the report. Embodiments of the presentinvention may provide guidance to the user to provide input, such asadditions to, deletions from, or modifications to the structured report120 to cause the structured report 120 to conform to the best practicesor to reduce the extent to which the structured report 120 fails toconform to the best practices.

Such guidance may be repeated for each of a plurality of best practices,and the kind and content of guidance may be the same or vary for eachsuch best practice. Similarly, the same best practice may be appliedmultiple times to the same structured report 120, such as by applyingthe same best practice to multiple portions of the same structuredreport 120, thereby resulting in multiple instances of guidance withinthe same structured report 120 based on the same best practice.

The method 200 includes inserting content into the structured document,based on the conclusion, to produce a modified structured document(230). The automatic speech recognition system 102 may update thestructured document 120 to include the user input; for example, thestructured document generator 104 may include functionality for updatinggenerated structured documents. In such an example, the structureddocument generator 104 may receive user input from the structureddocument analyzer 106 and update the structured document 120 with theuser input. As another example, the structured document analyzer 106 maytransmit an instruction to the structured document generator 104 togenerate a prompt within the structured document 120. The structureddocument generator 104 may render the modified structured document forreview by the user. FIG. 1D, described in greater detail below, providesan example of a modified structured document 121.

Although depicted in FIG. 1A as executing within the automatic speechrecognition system 102, the structured document generator 104 and thestructured document analyzer 106 may be provided as separate componentsin communication with the automatic speech recognition system 102.Referring now to FIG. 1C, and by way of example, the automatic speechrecognition system 102 may transmit a transcription 108 of an audiosignal to a stand-alone separate structured document generator 104,which in turn may transmit a structured document 120 to the structureddocument analyzer 106. In some embodiments, the structured documentgenerator 104 and the structured document analyzer 106 may be providedas part of a report generation component (not shown); for example, thestructured document generator 104 and the structured document analyzer106 may be provided as plug-ins, add-ons or other extensions to softwarefor generating components.

Embodiments of the present invention may provide output to the user toprompt the user to provide the input mentioned above for revising thestructured report 120. Such prompting output may take any of a varietyof forms. For example, a prompt (such as a window or a dialog box) thatis distinct from the rendering of the report itself may be displayed tothe user to prompt the user to provide input (e.g., by displaying thequestion “Was a foot exam performed on the patient?”). The user mayprovide such input in response to the distinct prompt, in response towhich the system may update the structured report 120 accordingly (suchas by adding a word, phrase, or sentence to the report representing theuser's input, or by checking off an appropriate box in the report). Theuser may provide the input in freeform or in a structured form; forexample, where the prompt includes an open-ended question, the user mayprovide the input in freeform. As an alternative example, when theprompt includes a closed question, the user may provide the input in astructured form. The form of the input provided in response to theprompt may differ from the form originally used to generate thestructured document 120; for example, the structured document 120 mayhave been generated based on freeform speech, while the prompt mayprompt for and receive input in the form of structured data, or viceversa.

As another example, a prompt may be displayed within the rendering ofthe report itself. Such a prompt may, for example, take the form of textappended to or inserted into the rendering of the report at anappropriate location. For example, if application of a best practicerule leads to the conclusion that the report is missing informationabout whether a foot exam was performed on the patient, and if thereport contains a section on procedures performed on the patient duringthe current visit, then a prompt such as “Foot exam performed?” may beinserted into that section. The text input cursor may then be positionedimmediately after this prompt, or the user may otherwise be notified ofthe prompt and given an opportunity to provide input directly into thedocument (such as by typing text) after the prompt.

Upon receiving input from the user, the system may update the report toinclude the input. For example, the system may insert the user inputinto the report substantially at or near the location of the promptwithin the structured document 120; in such an example, the system mayeither maintain the prompt or remove the prompt from the location.

As another example, the prompt may take the form of a form field, suchas a text field, check box, or dropdown list, into which the user maydirectly provide input in response to the prompt. An appropriate label(such as “Foot exam performed?”) may be displayed near the form field toguide the user in providing input into the form field. The user may thenprovide input directly into the form field to cause the structureddocument 120 to be updated in accordance with the corresponding bestpractice. Referring to FIG. 1D, a block diagram depicts one example of amodified structured document 121. As shown in the example depicted inFIG. 1D, a modified structured document 121 may include a plurality ofportions (which may also be referred to as sub-templates, sub-portionsor document components). In the example shown in FIG. 1D, the modifiedstructured document 121 is a version of the structured document 120 andincludes the first portion 122, including information 124, and thesecond portion 126, which does not include any information. However, inthe modified structured document 121, unlike in the structured document120, the second portion 126 includes a prompt 128 and a label 130. Theprompt 128 in this example is a text field into which a user may providemissing information. The label 130, displayed near the prompt 128, drawsattention to the prompt 128 and provides guidance as to a type ofinformation requested.

More generally, embodiments of the present invention may be containedwithin and/or operate in conjunction with a report generation procedure.Prompts provided by embodiments of the present invention may be part ofand integrated into the report generation procedure. As a particularexample, prompts may be integrated into the report itself. For example,as described elsewhere herein, as a report is being generated (andtherefore after part of the report has been generated but before theentire report has been generated), any of the prompts disclosed hereinmay be provided to the user. Such prompts may be added or otherwiseintegrated into the report as the report is being generated. Similarly,input provided in response to such prompts may be added to or otherwiseused to generate data that is added to the report as the report is beinggenerated.

As one example of the above, a prompt may be a report sub-template, andsuch a sub-template may be inserted into the report while the report isbeing generated. A report sub-template may, for example, include one ormore of a plurality of any kind(s) of form fields. For example, if anembodiment of the present invention determines that a particular portionof the report describes or otherwise relates to a particular type ofmedical procedure, in response to such a determination a reportsub-template corresponding to the particular type of medical proceduremay be identified and inserted into the report at the current locationwithin the report. Such an inserted report sub-template may includecontent (e.g., text) that is added to the report and/or form fields (orother kinds of prompts) to obtain input from the user to insert into thereport within the inserted report sub-template. The report sub-templateand any data entered by users into the report sub-template may becomepart of the final report. As in the examples provided above regardinginserting, into the structured document 120, input provided in responseto a prompt, the system may receive input from a user in response to thereport sub-template and incorporate the user input into the reportsub-template; and, as above, the system may determine to maintain orremove the prompt after the insertion of the user input. In examples inwhich the prompt is provided as a user interface element (e.g., a windowdisplaying text, the window rendered as part of the report generationsystem), the system may determine whether to continue rendering the userinterface element or to remove the user interface element from a displayafter the user input has been received.

As described above, the system may prompt the user to provide inputrepresenting missing information. For example, when a best practiceindicates that a particular type of content (such as a particularconcept, e.g., report section or fact) should be included in aparticular type of report, but the structured document analyzer 106determines that the structured document 120 does not contain theparticular type of content, the content is said to be missing from thereport. By way of example, if a best practice requires that a type ofreport include information indicating that a foot examination wasperformed on a patient but the structured document 120 does not includeinformation indicating that a foot exam was performed, then informationrelating to a foot exam is said to be “missing” from the report.

However, embodiments of the present invention are not limited toprompting the user to provide input representing missing information. Asanother example, embodiments of the present invention may automaticallyupdate the structured report 120 with the missing information, anestimate of the missing information, or an indication that suchinformation is missing, without receiving input from the user. Forexample, if the structured document analyzer 106 determines that tocomply with a particular best practice, the report is required toindicate whether a foot exam was performed and the report does notindicate whether a foot exam was performed, embodiments of the presentinvention may take any of a variety of actions, such as updating thereport to indicate that no information is available about whether a footexam was performed (e.g., by inserting the text “Foot exam performed? Noinformation available”), or by retrieving information about whether afoot exam was performed from an electronic medical record associatedwith the same patient and inserting that information automatically intothe report (e.g., by inserting the text “Foot exam performed? Yes”) intothe report. As another example, the system may prompt a user to take anaction. For instance; the structured document analyzer 106 may determinewhether a fact represented by the structured document 120 complies withthe best practice; if the described facts are determined not to complywith the best practice, then the system may prompt the user to take anaction that complies with the best practice. As an example, the systemmay prompt a reviewer of the structured document 120 to perform a footexam in an embodiment in which the structured document 120 is beinggenerated during a patient visit; the system may also prompt a reviewerof the structured document 120 to schedule, or arrange to havescheduled, a follow-up appointment with a patient to take an additionalaction (such as to perform a foot exam). The system may also prompt areviewer of the structured document 120 to follow up with a practitionerto determine how to address the missing information (for example, a userreviewing the structured document 120 may be prompted to contact thephysician who originally generated the audio signals and determine howthe physician prefers to obtain the missing information or complete anincomplete task). In some embodiments, therefore, the system prompts ahuman user to take an action, receives input from the human user, theinput indicating a status of the action, and inserts the input ascontent into the structured document 120. As with the examples above,such automatically generated information could be inserted into thestructured report 120 in other ways, such as by inserting it into formfields or using it to provide input to user interface controls such ascheckboxes or dropdown lists.

Any information inserted automatically into a report may be marked as“automatically generated.” When the report is rendered, suchautomatically generated information may be flagged as such, such as byhighlighting such information in a particular color, to call attentionto the fact that such information was generated automatically and notinput manually by a human. The user may even be specifically prompted toreview and, if necessary, edit such information.

Any of the techniques described above may be performed while aparticular report is being transcribed or after the report has beentranscribed. For example, after a particular portion of a report hasbeen transcribed, best practices may be applied to that portion of thereport in any of the ways disclosed above, even as the user continues todictate additional portions of the report and even as such portions aretranscribed to generated additional text.

Furthermore, any of the techniques described above may be used inconnection with a single user or multiple users across any number ofcomputing devices. For example, a single user may dictate a report andalso provide additional input in response to prompts generated based onapplication of best practices to the report. As another example, a firstuser may dictate the report and a second user may provide additionalinput in response to prompts generated based on application of bestpractices to the report.

Embodiments of the present invention have a variety of advantages. Forexample, embodiments of the present invention combine some of theadvantages of freeform input modalities with some of the advantages ofstructured input modalities, while reducing or eliminating some of thedisadvantages of both. In particular, embodiments of the presentinvention combine the ability of freeform input modalities to enableusers to provide unbiased and nuanced input with the ability ofstructured input modalities to enforce requirements that certain kindsof data be input. One way in which embodiments of the present inventionachieve this result is by enabling the user to first provide input usinga freeform input modality, then determining whether the input includesan indication of compliance with one or more best practices, and thenextending the resulting report (either automatically or based onadditional input from the user) based on conclusions drawn from thedetermination. The report extension may involve obtaining input from theuser using a structured input modality, such as by obtaining input fromthe user in a form field. By requesting and obtaining such structuredinput from the user only if and when necessary, embodiments of thepresent invention avoid predisposing the user toward providing inputthat is biased in the way caused by conventional structured inputmodalities.

Another benefit of embodiments of the present invention is that they mayincrease the accuracy of the resulting report, either by guiding theuser toward providing more complete information that is compliant withbest practices, or by obtaining and inserting such information into thereport automatically. Reduced errors and higher degrees of completenesscan be particularly beneficial in contexts, such as medical reporting,in which the accuracy and completeness of reports can have an impact onhuman health and safety, and in which accurate and complete reports arenecessary to comply with regulations and to obtain reimbursement for theprocedures that resulted in the reports.

Yet another advantage of embodiments of the present invention is that byreminding a physician and/or other user to take a recommended orrequired action (such as performing a procedure on a patient), the usercan be reminded to take such action and thereby be more likely to takethe action. Even if the user is reminded of the action to take at a timewhen it is no longer possible to take the action in connection with theevent that led to the creation of the report (such as a patient visit),the user may be reminded of the need to take the action in similarcircumstances in the future. In this way, embodiments of the presentinvention may serve to educate users and to increase the likelihood thatthey will take recommended and/or required actions in the future.

Another advantage of embodiments of the present invention is that theymay be used to encourage or require users to provide input that isuseful and/or required for subsequent processing, such as informationthat is required to generate a bill for reimbursement of healthcareservices. For example, if a report is input solely in the form offreeform text using conventional methods, it might be difficult toextract information needed for billing from such text. For example, if afreeform text report describes a surgery performed on a patient and, inthe course of describing the surgery, describes not only stents thatactually were inserted into the patient but also stents that wereattempted to be inserted into the patient without success, it might bedifficult or impossible to automatically extract from such a report thenumber of stents that actually were inserted into the patient. Yet itmay be necessary to provide such a number to generate a bill that may beused to obtain reimbursement for the surgery. If instead, usingembodiments of the present invention, the physician or other user isrequired to provide the number of stents actually inserted as a discretedata element using a structured input modality, then the bill may begenerated automatically because the system has enforced the requirementthat information necessary to generate the bill be provided as input.The same logic applies to any information that is contained within adocument but is difficult to extract discretely and automatically.

Yet another benefit of embodiments of the present invention is that theymay be used to reconcile existing stored data (such as discrete data,e.g., data stored in an EMR or other database record) with data inputinto a report. For example, if the dictating physician indicates that apatient has uncontrolled diabetes and existing data (e.g., data for thepatient stored in an EMR) already indicates that the patient hasdiabetes but does not indicate whether the diabetes is uncontrolled,embodiments of the present invention may be used to revise the existingdata (e.g., EMR) about the patient to specify that the patient'sdiabetes is uncontrolled.

It is to be understood that although the invention has been describedabove in terms of particular embodiments, the foregoing embodiments areprovided as illustrative only, and do not limit or define the scope ofthe invention. Various other embodiments, including but not limited tothe following, are also within the scope of the claims. For example,elements and components described herein may be further divided intoadditional components or joined together to form fewer components forperforming the same functions.

The techniques described above may be implemented, for example, inhardware, software tangibly stored on a computer-readable medium,firmware, or any combination thereof. The techniques described above maybe implemented in one or more computer programs executing on aprogrammable computer including a processor, a storage medium readableby the processor (including, for example, volatile and non-volatilememory and/or storage elements), at least one input device, and at leastone output device. Program code may be applied to input entered usingthe input device to perform the functions described and to generateoutput. The output may be provided to one or more output devices.

Each computer program within the scope of the claims below may beimplemented in any programming language, such as assembly language,machine language, a high-level procedural programming language, or anobject-oriented programming language. The programming language may, forexample, be a compiled or interpreted programming language.

Each such computer program may be implemented in a computer programproduct tangibly embodied in a machine-readable storage device forexecution by a computer processor. Method steps of the invention may beperformed by a computer processor executing a program tangibly embodiedon a computer-readable medium to perform functions of the invention byoperating on input and generating output. Suitable processors include,by way of example, both general and special purpose microprocessors.Generally, the processor receives instructions and data from a read-onlymemory and/or a random access memory. Storage devices suitable fortangibly embodying computer program instructions include, for example,all forms of non-volatile memory, such as semiconductor memory devices,including EPROM, EEPROM, and flash memory devices; magnetic disks suchas internal hard disks and removable disks; magneto-optical disks; andCD-ROMs. Any of the foregoing may be supplemented by, or incorporatedin, specially-designed ASICs (application-specific integrated circuits)or FPGAs (Field-Programmable Gate Arrays). A computer can generally alsoreceive programs and data from a storage medium such as an internal disk(not shown) or a removable disk. These elements will also be found in aconventional desktop or workstation computer as well as other computerssuitable for executing computer programs implementing the methodsdescribed herein, which may be used in conjunction with any digitalprint engine or marking engine, display monitor, or other raster outputdevice capable of producing color or gray scale pixels on paper, film,display screen, or other output medium.

What is claimed:
 1. A computer-implemented method performed by at leastone computer processor, the method comprising: (A) applying automaticspeech recognition to an audio signal to produce a structured documentrepresenting contents of the audio signal; (B) determining whether thestructured document includes an indication of compliance for each of aplurality of best practices to produce a conclusion, the plurality ofbest practices related to at least one action required to be takenbefore completion of the structured document, at least one of theplurality of best practices including at least one of a heuristic and aprocedure for drawing a conclusion about whether the structured documentfails to comply with a standard applicable to the structured document;and (C) inserting content into the structured document, based on theconclusion, to produce a modified structured document, wherein insertingfurther comprises: (C)(1) obtaining the content from a data sourcewithout human input; and (C)(2) inserting the content into thestructured document.